Computing power has become increasingly decentralized, providing for increased efficiency and scalability. Accordingly, data storage services are also moving to a distributed, decentralized model in which storage servers are allocated in such a way as to replicate a given data object across multiple such servers, thereby providing increased durability, scalability, and performance. However, when large numbers of data objects are stored across such multiple servers, retrieving a list of the data objects can be slow and difficult to parallelize. As storage demands increase, efficient methods for tracking and listing the data objects in a distributed processing framework file system become important.